Search

Your search keyword '"Altes A"' showing total 7,202 results
Start Over Author "Altes A"

Refine your results

more »

more »

more »

more »

more »

more »

more »
7,202 results on '"Altes A"'

1. The 2024 Brain Tumor Segmentation (BraTS) Challenge: Glioma Segmentation on Post-treatment MRI

Author

de Verdier, Maria Correia, Saluja, Rachit, Gagnon, Louis, LaBella, Dominic, Baid, Ujjwall, Tahon, Nourel Hoda, Foltyn-Dumitru, Martha, Zhang, Jikai, Alafif, Maram, Baig, Saif, Chang, Ken, D'Anna, Gennaro, Deptula, Lisa, Gupta, Diviya, Haider, Muhammad Ammar, Hussain, Ali, Iv, Michael, Kontzialis, Marinos, Manning, Paul, Moodi, Farzan, Nunes, Teresa, Simon, Aaron, Sollmann, Nico, Vu, David, Adewole, Maruf, Albrecht, Jake, Anazodo, Udunna, Chai, Rongrong, Chung, Verena, Faghani, Shahriar, Farahani, Keyvan, Kazerooni, Anahita Fathi, Iglesias, Eugenio, Kofler, Florian, Li, Hongwei, Linguraru, Marius George, Menze, Bjoern, Moawad, Ahmed W., Velichko, Yury, Wiestler, Benedikt, Altes, Talissa, Basavasagar, Patil, Bendszus, Martin, Brugnara, Gianluca, Cho, Jaeyoung, Dhemesh, Yaseen, Fields, Brandon K. K., Garrett, Filip, Gass, Jaime, Hadjiiski, Lubomir, Hattangadi-Gluth, Jona, Hess, Christopher, Houk, Jessica L., Isufi, Edvin, Layfield, Lester J., Mastorakos, George, Mongan, John, Nedelec, Pierre, Nguyen, Uyen, Oliva, Sebastian, Pease, Matthew W., Rastogi, Aditya, Sinclair, Jason, Smith, Robert X., Sugrue, Leo P., Thacker, Jonathan, Vidic, Igor, Villanueva-Meyer, Javier, White, Nathan S., Aboian, Mariam, Conte, Gian Marco, Dale, Anders, Sabuncu, Mert R., Seibert, Tyler M., Weinberg, Brent, Abayazeed, Aly, Huang, Raymond, Turk, Sevcan, Rauschecker, Andreas M., Farid, Nikdokht, Vollmuth, Philipp, Nada, Ayman, Bakas, Spyridon, Calabrese, Evan, and Rudie, Jeffrey D.

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Gliomas are the most common malignant primary brain tumors in adults and one of the deadliest types of cancer. There are many challenges in treatment and monitoring due to the genetic diversity and high intrinsic heterogeneity in appearance, shape, histology, and treatment response. Treatments include surgery, radiation, and systemic therapies, with magnetic resonance imaging (MRI) playing a key role in treatment planning and post-treatment longitudinal assessment. The 2024 Brain Tumor Segmentation (BraTS) challenge on post-treatment glioma MRI will provide a community standard and benchmark for state-of-the-art automated segmentation models based on the largest expert-annotated post-treatment glioma MRI dataset. Challenge competitors will develop automated segmentation models to predict four distinct tumor sub-regions consisting of enhancing tissue (ET), surrounding non-enhancing T2/fluid-attenuated inversion recovery (FLAIR) hyperintensity (SNFH), non-enhancing tumor core (NETC), and resection cavity (RC). Models will be evaluated on separate validation and test datasets using standardized performance metrics utilized across the BraTS 2024 cluster of challenges, including lesion-wise Dice Similarity Coefficient and Hausdorff Distance. Models developed during this challenge will advance the field of automated MRI segmentation and contribute to their integration into clinical practice, ultimately enhancing patient care., Comment: 10 pages, 4 figures, 1 table

Published
2024

2. Analysis of the BraTS 2023 Intracranial Meningioma Segmentation Challenge

Author

LaBella, Dominic, Baid, Ujjwal, Khanna, Omaditya, McBurney-Lin, Shan, McLean, Ryan, Nedelec, Pierre, Rashid, Arif, Tahon, Nourel Hoda, Altes, Talissa, Bhalerao, Radhika, Dhemesh, Yaseen, Godfrey, Devon, Hilal, Fathi, Floyd, Scott, Janas, Anastasia, Kazerooni, Anahita Fathi, Kirkpatrick, John, Kent, Collin, Kofler, Florian, Leu, Kevin, Maleki, Nazanin, Menze, Bjoern, Pajot, Maxence, Reitman, Zachary J., Rudie, Jeffrey D., Saluja, Rachit, Velichko, Yury, Wang, Chunhao, Warman, Pranav, Adewole, Maruf, Albrecht, Jake, Anazodo, Udunna, Anwar, Syed Muhammad, Bergquist, Timothy, Chen, Sully Francis, Chung, Verena, Conte, Gian-Marco, Dako, Farouk, Eddy, James, Ezhov, Ivan, Khalili, Nastaran, Iglesias, Juan Eugenio, Jiang, Zhifan, Johanson, Elaine, Van Leemput, Koen, Li, Hongwei Bran, Linguraru, Marius George, Liu, Xinyang, Mahtabfar, Aria, Meier, Zeke, Moawad, Ahmed W., Mongan, John, Piraud, Marie, Shinohara, Russell Takeshi, Wiggins, Walter F., Abayazeed, Aly H., Akinola, Rachel, Jakab, András, Bilello, Michel, de Verdier, Maria Correia, Crivellaro, Priscila, Davatzikos, Christos, Farahani, Keyvan, Freymann, John, Hess, Christopher, Huang, Raymond, Lohmann, Philipp, Moassefi, Mana, Pease, Matthew W., Vollmuth, Phillipp, Sollmann, Nico, Diffley, David, Nandolia, Khanak K., Warren, Daniel I., Hussain, Ali, Fehringer, Pascal, Bronstein, Yulia, Deptula, Lisa, Stein, Evan G., Taherzadeh, Mahsa, de Oliveira, Eduardo Portela, Haughey, Aoife, Kontzialis, Marinos, Saba, Luca, Turner, Benjamin, Brüßeler, Melanie M. T., Ansari, Shehbaz, Gkampenis, Athanasios, Weiss, David Maximilian, Mansour, Aya, Shawali, Islam H., Yordanov, Nikolay, Stein, Joel M., Hourani, Roula, Moshebah, Mohammed Yahya, Abouelatta, Ahmed Magdy, Rizvi, Tanvir, Willms, Klara, Martin, Dann C., Okar, Abdullah, D'Anna, Gennaro, Taha, Ahmed, Sharifi, Yasaman, Faghani, Shahriar, Kite, Dominic, Pinho, Marco, Haider, Muhammad Ammar, Aristizabal, Alejandro, Karargyris, Alexandros, Kassem, Hasan, Pati, Sarthak, Sheller, Micah, Alonso-Basanta, Michelle, Villanueva-Meyer, Javier, Rauschecker, Andreas M., Nada, Ayman, Aboian, Mariam, Flanders, Adam E., Wiestler, Benedikt, Bakas, Spyridon, and Calabrese, Evan

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

We describe the design and results from the BraTS 2023 Intracranial Meningioma Segmentation Challenge. The BraTS Meningioma Challenge differed from prior BraTS Glioma challenges in that it focused on meningiomas, which are typically benign extra-axial tumors with diverse radiologic and anatomical presentation and a propensity for multiplicity. Nine participating teams each developed deep-learning automated segmentation models using image data from the largest multi-institutional systematically expert annotated multilabel multi-sequence meningioma MRI dataset to date, which included 1000 training set cases, 141 validation set cases, and 283 hidden test set cases. Each case included T2, T2/FLAIR, T1, and T1Gd brain MRI sequences with associated tumor compartment labels delineating enhancing tumor, non-enhancing tumor, and surrounding non-enhancing T2/FLAIR hyperintensity. Participant automated segmentation models were evaluated and ranked based on a scoring system evaluating lesion-wise metrics including dice similarity coefficient (DSC) and 95% Hausdorff Distance. The top ranked team had a lesion-wise median dice similarity coefficient (DSC) of 0.976, 0.976, and 0.964 for enhancing tumor, tumor core, and whole tumor, respectively and a corresponding average DSC of 0.899, 0.904, and 0.871, respectively. These results serve as state-of-the-art benchmarks for future pre-operative meningioma automated segmentation algorithms. Additionally, we found that 1286 of 1424 cases (90.3%) had at least 1 compartment voxel abutting the edge of the skull-stripped image edge, which requires further investigation into optimal pre-processing face anonymization steps., Comment: 16 pages, 11 tables, 10 figures, MICCAI

Published
2024

3. A multi-institutional meningioma MRI dataset for automated multi-sequence image segmentation.

Author

LaBella, Dominic, Khanna, Omaditya, McBurney-Lin, Shan, Mclean, Ryan, Nedelec, Pierre, Rashid, Arif, Tahon, Nourel, Altes, Talissa, Baid, Ujjwal, Bhalerao, Radhika, Dhemesh, Yaseen, Floyd, Scott, Godfrey, Devon, Hilal, Fathi, Janas, Anastasia, Kazerooni, Anahita, Kent, Collin, Kirkpatrick, John, Kofler, Florian, Leu, Kevin, Maleki, Nazanin, Menze, Bjoern, Pajot, Maxence, Reitman, Zachary, Rudie, Jeffrey, Saluja, Rachit, Velichko, Yury, Wang, Chunhao, Warman, Pranav, Sollmann, Nico, Diffley, David, Nandolia, Khanak, Warren, Daniel, Hussain, Ali, Fehringer, John, Bronstein, Yulia, Deptula, Lisa, Stein, Evan, Taherzadeh, Mahsa, Portela de Oliveira, Eduardo, Haughey, Aoife, Kontzialis, Marinos, Saba, Luca, Turner, Benjamin, Brüßeler, Melanie, Ansari, Shehbaz, Gkampenis, Athanasios, Weiss, David, Mansour, Aya, Shawali, Islam, Yordanov, Nikolay, Stein, Joel, Hourani, Roula, Moshebah, Mohammed, Abouelatta, Ahmed, Rizvi, Tanvir, Willms, Klara, Martin, Dann, Okar, Abdullah, DAnna, Gennaro, Taha, Ahmed, Sharifi, Yasaman, Faghani, Shahriar, Kite, Dominic, Pinho, Marco, Haider, Muhammad, Alonso-Basanta, Michelle, Rauschecker, Andreas, Nada, Ayman, Aboian, Mariam, Flanders, Adam, Bakas, Spyridon, Calabrese, Evan, and Villanueva-Meyer, Javier

Subjects
Meningioma, Humans, Magnetic Resonance Imaging, Meningeal Neoplasms, Male, Female, Image Processing, Computer-Assisted, Middle Aged, Aged
Abstract

Meningiomas are the most common primary intracranial tumors and can be associated with significant morbidity and mortality. Radiologists, neurosurgeons, neuro-oncologists, and radiation oncologists rely on brain MRI for diagnosis, treatment planning, and longitudinal treatment monitoring. However, automated, objective, and quantitative tools for non-invasive assessment of meningiomas on multi-sequence MR images are not available. Here we present the BraTS Pre-operative Meningioma Dataset, as the largest multi-institutional expert annotated multilabel meningioma multi-sequence MR image dataset to date. This dataset includes 1,141 multi-sequence MR images from six sites, each with four structural MRI sequences (T2-, T2/FLAIR-, pre-contrast T1-, and post-contrast T1-weighted) accompanied by expert manually refined segmentations of three distinct meningioma sub-compartments: enhancing tumor, non-enhancing tumor, and surrounding non-enhancing T2/FLAIR hyperintensity. Basic demographic data are provided including age at time of initial imaging, sex, and CNS WHO grade. The goal of releasing this dataset is to facilitate the development of automated computational methods for meningioma segmentation and expedite their incorporation into clinical practice, ultimately targeting improvement in the care of meningioma patients.

Published
2024

5. The implications of the COVID-19 pandemic on eating disorder features and comorbid psychopathology among adolescents with anorexia nervosa and matched controls: a comparative cohort design study

Author

Bracké, Katrien, Steegers, Cathelijne, van der Harst, Tess, Pons, Rozemarijn, Legerstee, Jeroen, Dierckx, Bram, de Nijs, Pieter, Bax-van Berkel, Marieke, van Elburg, Annemarie, Hekkelaan, Marion, Hokke, Joke, de Jong-Zuidema, Hetty, Korthals Altes, Lucas, Lengton-van der Spil, Farida, Luijkx, Judith, Schuurmans, Femke, Smeets, Carien, van Wijk, Lia, Woltering, Claire, Vernooij, Meike, Hillegers, Manon, White, Tonya, and Dieleman, Gwen

Published
2024
Full Text
View/download PDF

6. The Brain Tumor Segmentation (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRI

Author

Moawad, Ahmed W., Janas, Anastasia, Baid, Ujjwal, Ramakrishnan, Divya, Saluja, Rachit, Ashraf, Nader, Maleki, Nazanin, Jekel, Leon, Yordanov, Nikolay, Fehringer, Pascal, Gkampenis, Athanasios, Amiruddin, Raisa, Manteghinejad, Amirreza, Adewole, Maruf, Albrecht, Jake, Anazodo, Udunna, Aneja, Sanjay, Anwar, Syed Muhammad, Bergquist, Timothy, Chiang, Veronica, Chung, Verena, Conte, Gian Marco, Dako, Farouk, Eddy, James, Ezhov, Ivan, Khalili, Nastaran, Farahani, Keyvan, Iglesias, Juan Eugenio, Jiang, Zhifan, Johanson, Elaine, Kazerooni, Anahita Fathi, Kofler, Florian, Krantchev, Kiril, LaBella, Dominic, Van Leemput, Koen, Li, Hongwei Bran, Linguraru, Marius George, Liu, Xinyang, Meier, Zeke, Menze, Bjoern H, Moy, Harrison, Osenberg, Klara, Piraud, Marie, Reitman, Zachary, Shinohara, Russell Takeshi, Wang, Chunhao, Wiestler, Benedikt, Wiggins, Walter, Shafique, Umber, Willms, Klara, Avesta, Arman, Bousabarah, Khaled, Chakrabarty, Satrajit, Gennaro, Nicolo, Holler, Wolfgang, Kaur, Manpreet, LaMontagne, Pamela, Lin, MingDe, Lost, Jan, Marcus, Daniel S., Maresca, Ryan, Merkaj, Sarah, Pedersen, Gabriel Cassinelli, von Reppert, Marc, Sotiras, Aristeidis, Teytelboym, Oleg, Tillmans, Niklas, Westerhoff, Malte, Youssef, Ayda, Godfrey, Devon, Floyd, Scott, Rauschecker, Andreas, Villanueva-Meyer, Javier, Pfluger, Irada, Cho, Jaeyoung, Bendszus, Martin, Brugnara, Gianluca, Cramer, Justin, Perez-Carillo, Gloria J. Guzman, Johnson, Derek R., Kam, Anthony, Kwan, Benjamin Yin Ming, Lai, Lillian, Lall, Neil U., Memon, Fatima, Krycia, Mark, Patro, Satya Narayana, Petrovic, Bojan, So, Tiffany Y., Thompson, Gerard, Wu, Lei, Schrickel, E. Brooke, Bansal, Anu, Barkhof, Frederik, Besada, Cristina, Chu, Sammy, Druzgal, Jason, Dusoi, Alexandru, Farage, Luciano, Feltrin, Fabricio, Fong, Amy, Fung, Steve H., Gray, R. Ian, Ikuta, Ichiro, Iv, Michael, Postma, Alida A., Mahajan, Amit, Joyner, David, Krumpelman, Chase, Letourneau-Guillon, Laurent, Lincoln, Christie M., Maros, Mate E., Miller, Elka, Moron, Fanny, Nimchinsky, Esther A., Ozsarlak, Ozkan, Patel, Uresh, Rohatgi, Saurabh, Saha, Atin, Sayah, Anousheh, Schwartz, Eric D., Shih, Robert, Shiroishi, Mark S., Small, Juan E., Tanwar, Manoj, Valerie, Jewels, Weinberg, Brent D., White, Matthew L., Young, Robert, Zohrabian, Vahe M., Azizova, Aynur, Bruseler, Melanie Maria Theresa, Ghonim, Mohanad, Ghonim, Mohamed, Okar, Abdullah, Pasquini, Luca, Sharifi, Yasaman, Singh, Gagandeep, Sollmann, Nico, Soumala, Theodora, Taherzadeh, Mahsa, Vollmuth, Philipp, Foltyn-Dumitru, Martha, Malhotra, Ajay, Abayazeed, Aly H., Dellepiane, Francesco, Lohmann, Philipp, Perez-Garcia, Victor M., Elhalawani, Hesham, de Verdier, Maria Correia, Al-Rubaiey, Sanaria, Armindo, Rui Duarte, Ashraf, Kholod, Asla, Moamen M., Badawy, Mohamed, Bisschop, Jeroen, Lomer, Nima Broomand, Bukatz, Jan, Chen, Jim, Cimflova, Petra, Corr, Felix, Crawley, Alexis, Deptula, Lisa, Elakhdar, Tasneem, Shawali, Islam H., Faghani, Shahriar, Frick, Alexandra, Gulati, Vaibhav, Haider, Muhammad Ammar, Hierro, Fatima, Dahl, Rasmus Holmboe, Jacobs, Sarah Maria, Hsieh, Kuang-chun Jim, Kandemirli, Sedat G., Kersting, Katharina, Kida, Laura, Kollia, Sofia, Koukoulithras, Ioannis, Li, Xiao, Abouelatta, Ahmed, Mansour, Aya, Maria-Zamfirescu, Ruxandra-Catrinel, Marsiglia, Marcela, Mateo-Camacho, Yohana Sarahi, McArthur, Mark, McDonnell, Olivia, McHugh, Maire, Moassefi, Mana, Morsi, Samah Mostafa, Munteanu, Alexander, Nandolia, Khanak K., Naqvi, Syed Raza, Nikanpour, Yalda, Alnoury, Mostafa, Nouh, Abdullah Mohamed Aly, Pappafava, Francesca, Patel, Markand D., Petrucci, Samantha, Rawie, Eric, Raymond, Scott, Roohani, Borna, Sabouhi, Sadeq, Sanchez-Garcia, Laura M., Shaked, Zoe, Suthar, Pokhraj P., Altes, Talissa, Isufi, Edvin, Dhemesh, Yaseen, Gass, Jaime, Thacker, Jonathan, Tarabishy, Abdul Rahman, Turner, Benjamin, Vacca, Sebastiano, Vilanilam, George K., Warren, Daniel, Weiss, David, Worede, Fikadu, Yousry, Sara, Lerebo, Wondwossen, Aristizabal, Alejandro, Karargyris, Alexandros, Kassem, Hasan, Pati, Sarthak, Sheller, Micah, Link, Katherine E., Calabrese, Evan, Tahon, Nourel hoda, Nada, Ayman, Velichko, Yuri S., Bakas, Spyridon, Rudie, Jeffrey D., and Aboian, Mariam

Subjects
Quantitative Biology - Other Quantitative Biology, Electrical Engineering and Systems Science - Image and Video Processing
Abstract

The translation of AI-generated brain metastases (BM) segmentation into clinical practice relies heavily on diverse, high-quality annotated medical imaging datasets. The BraTS-METS 2023 challenge has gained momentum for testing and benchmarking algorithms using rigorously annotated internationally compiled real-world datasets. This study presents the results of the segmentation challenge and characterizes the challenging cases that impacted the performance of the winning algorithms. Untreated brain metastases on standard anatomic MRI sequences (T1, T2, FLAIR, T1PG) from eight contributed international datasets were annotated in stepwise method: published UNET algorithms, student, neuroradiologist, final approver neuroradiologist. Segmentations were ranked based on lesion-wise Dice and Hausdorff distance (HD95) scores. False positives (FP) and false negatives (FN) were rigorously penalized, receiving a score of 0 for Dice and a fixed penalty of 374 for HD95. Eight datasets comprising 1303 studies were annotated, with 402 studies (3076 lesions) released on Synapse as publicly available datasets to challenge competitors. Additionally, 31 studies (139 lesions) were held out for validation, and 59 studies (218 lesions) were used for testing. Segmentation accuracy was measured as rank across subjects, with the winning team achieving a LesionWise mean score of 7.9. Common errors among the leading teams included false negatives for small lesions and misregistration of masks in space.The BraTS-METS 2023 challenge successfully curated well-annotated, diverse datasets and identified common errors, facilitating the translation of BM segmentation across varied clinical environments and providing personalized volumetric reports to patients undergoing BM treatment.

Published
2023

7. The ASNR-MICCAI Brain Tumor Segmentation (BraTS) Challenge 2023: Intracranial Meningioma

Author

LaBella, Dominic, Adewole, Maruf, Alonso-Basanta, Michelle, Altes, Talissa, Anwar, Syed Muhammad, Baid, Ujjwal, Bergquist, Timothy, Bhalerao, Radhika, Chen, Sully, Chung, Verena, Conte, Gian-Marco, Dako, Farouk, Eddy, James, Ezhov, Ivan, Godfrey, Devon, Hilal, Fathi, Familiar, Ariana, Farahani, Keyvan, Iglesias, Juan Eugenio, Jiang, Zhifan, Johanson, Elaine, Kazerooni, Anahita Fathi, Kent, Collin, Kirkpatrick, John, Kofler, Florian, Van Leemput, Koen, Li, Hongwei Bran, Liu, Xinyang, Mahtabfar, Aria, McBurney-Lin, Shan, McLean, Ryan, Meier, Zeke, Moawad, Ahmed W, Mongan, John, Nedelec, Pierre, Pajot, Maxence, Piraud, Marie, Rashid, Arif, Reitman, Zachary, Shinohara, Russell Takeshi, Velichko, Yury, Wang, Chunhao, Warman, Pranav, Wiggins, Walter, Aboian, Mariam, Albrecht, Jake, Anazodo, Udunna, Bakas, Spyridon, Flanders, Adam, Janas, Anastasia, Khanna, Goldey, Linguraru, Marius George, Menze, Bjoern, Nada, Ayman, Rauschecker, Andreas M, Rudie, Jeff, Tahon, Nourel Hoda, Villanueva-Meyer, Javier, Wiestler, Benedikt, and Calabrese, Evan

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

Meningiomas are the most common primary intracranial tumor in adults and can be associated with significant morbidity and mortality. Radiologists, neurosurgeons, neuro-oncologists, and radiation oncologists rely on multiparametric MRI (mpMRI) for diagnosis, treatment planning, and longitudinal treatment monitoring; yet automated, objective, and quantitative tools for non-invasive assessment of meningiomas on mpMRI are lacking. The BraTS meningioma 2023 challenge will provide a community standard and benchmark for state-of-the-art automated intracranial meningioma segmentation models based on the largest expert annotated multilabel meningioma mpMRI dataset to date. Challenge competitors will develop automated segmentation models to predict three distinct meningioma sub-regions on MRI including enhancing tumor, non-enhancing tumor core, and surrounding nonenhancing T2/FLAIR hyperintensity. Models will be evaluated on separate validation and held-out test datasets using standardized metrics utilized across the BraTS 2023 series of challenges including the Dice similarity coefficient and Hausdorff distance. The models developed during the course of this challenge will aid in incorporation of automated meningioma MRI segmentation into clinical practice, which will ultimately improve care of patients with meningioma.

Published
2023

8. Conditional diffusion-generated super-resolution for myocardial perfusion MRI

Author

Changyu Sun, Neha Goyal, Yu Wang, Darla L. Tharp, Senthil Kumar, and Talissa A. Altes

Subjects
super-resolution, myocardial perfusion MRI, deep learning, diffusion probabilistic models (DDPM), conditional generative model, dynamic contrast-enhanced MRI (DCE MRI), Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract

IntroductionMyocardial perfusion MRI is important for diagnosing coronary artery disease, but current clinical methods face challenges in balancing spatial resolution, temporal resolution, and slice coverage. Achieving broader slice coverage and higher temporal resolution is essential for accurately detecting abnormalities across different slice locations but remains difficult due to constraints in acquisition speed and heart rate variability. While techniques like parallel imaging and compressed sensing have significantly advanced perfusion imaging, they still suffer from noise amplification, residual artifacts, and potential temporal blurring due to the rapid transit of dynamic contrast vs. the temporal constraints of the reconstruction.MethodsThis study introduces a conditional diffusion-based generative model for myocardial perfusion MRI super resolution, addressing the trade-offs between spatiotemporal resolution and slice coverage. We adapted Denoising Diffusion Probabilistic Models (DDPM) to enhance low-resolution perfusion images into high-resolution outputs without requiring temporal regularization. The forward diffusion process introduces Gaussian noise incrementally, while the reverse process employs a U-Net architecture to progressively denoise the images, conditioned on the low-resolution input image.ResultsWe trained and validated the model on a retrospective dataset of dynamic contrast-enhanced (DCE) perfusion MRI, consisting of both stress and rest images from 47 patients with heart disease. Our results showed significant image quality improvements, with a 5.1% reduction in nRMSE, a 1.1% increase in PSNR, and a 2.2% boost in SSIM compared to GAN-based super-resolution method (P

Published
2025
Full Text
View/download PDF

9. Wikigender: A Machine Learning Model to Detect Gender Bias in Wikipedia

Author

Brun, Natalie Bolón, Kypraiou, Sofia, Altés, Natalia Gullón, and Barrios, Irene Petlacalco

Subjects
Computer Science - Computers and Society
Abstract

The way Wikipedia's contributors think can influence how they describe individuals resulting in a bias based on gender. We use a machine learning model to prove that there is a difference in how women and men are portrayed on Wikipedia. Additionally, we use the results of the model to obtain which words create bias in the overview of the biographies of the English Wikipedia. Using only adjectives as input to the model, we show that the adjectives used to portray women have a higher subjectivity than the ones used to describe men. Extracting topics from the overview using nouns and adjectives as input to the model, we obtain that women are related to family while men are related to business and sports., Comment: WikiWorkshop '20 Proc. of World Wide Web Conference

Published
2022

10. A literature review and evidence-based evaluation of the Dutch national immunisation schedule yield possibilities for improvements

Author

Pluijmaekers, A.J.M., Steens, A., Houweling, H., Rots, N.Y., Benschop, K.S.M., van Binnendijk, R.S., Bodewes, R., Brouwer, J.G.M., Buisman, A., Duizer, E., van Els, C.A.C.M., Hament, J.M., den Hartog, G., Kaaijk, P., Kerkhof, K., King, A.J., van der Klis, F.R.M., Korthals Altes, H., van der Maas, N.A.T., van Meijeren, D.L., Middeldorp, M., Rijnbende-Geraerts, S.D., Sanders, E.A.M., Veldhuijzen, I.K., Vlaanderen, E., Voordouw, A.C.G., Vos, E.R.A., de Wit, J., Woudenberg, T., van Vliet, J.A., and de Melker, H.E.

Published
2024
Full Text
View/download PDF

13. Hospital variation in quality indicators for patient blood management in total knee and hip arthroplasty: a retrospective cohort study

Author

Azparren, Alicia Aranguren, Gosálbez, Ana Abad, Faura, Ana, Plaza, Ana morales de la, Puig, Ana Ruiz, Caballero, Angel, Lavado, Ángel, Montserrat, Cadena Serramitja, Jericó, Carlos, Sanabria, Carmen Elena, Escribano, Cristina Martinez, Paraschiv, Dra.Violeta Turcu, Cerezo, Estefania, Méndez, Esther, Ponce, Esther Sancho, Ribas, Esther Vila, Parga, Eva Bassas, Jimeno Demuth, Francisco José, Moreno-Jimenez, Gemma, Montero, Gerardo Gómez, Cabezón, Gonzalo Azparren, Graciani, Ignacio de la Fuente, Ruiz, Inocencia Fornet, Martínez, Isabel Castrillo, Ortega Lucas, J. Enrique, Gorricho, Javier, Estévez, Javier Mata, Morales, Jordi Colomina, García-Erce, José Antonio, Campuzano Garcia, José Luis, Gonzalez-Rodriguez, Jose Luis, García-Gala, Jose M., Vagace, José Manuel, Ávila Idrovo, Laura Francisca, Almirante, Laura Martínez, Gonzalez del Castillo, Luz María, Pisano Blanco, M Aranzazu, Campos Peláez, M Isabel, Herranz Andrés, M Pilar, Conejo, Manel Romero, Ruiz Dãíaz, Maria Pilar, Díaz Comino, Maria Raquel, Navarro, Marina Canales, Albacar-Ingla, Marta, Mesa, Miguel Rey, Riera, Montserrat Torra, Ibarra, N., Pons, Natalia Gallench, López, Nuria Ruiz, Navarro, Pablo González, Austenrritt, Pamela Millacoy, Sorolla, Patricia Marzal, Perez, Pilar Arribas, Solves, Pilar, París, Raquel Tolós, Morell, Reis Drudis, Robles-Cedeño, René, Upegui Villegas, Rosa I., Alvarez, Sonsoles Aragón, Planella, Teresa, Dueñas, Virginia, Nuñez, Yolanda Cabanillas, Gómez, Yolanda Palacios, Garcia-Casanovas, Albert, Bisbe, Elvira, Garcia-Altes, Anna, Vizoso, Adria, Duran-Jorda, Xavier, Sanchez-Pedrosa, Guillermo, Barquero, Marta, Colomina, Maria J., and Basora, Misericordia

Published
2024
Full Text
View/download PDF

16. Minimalistic musings about the Standard Model

Author

Altes, Chris P. Korthals

Subjects
High Energy Physics - Phenomenology
Abstract

\hspace{2,0cm}{{\bf A tribute to Martinus Veltman 1931-2021}} Martinus ("Tini") Veltman 's early contributions to the Standard Model were essential for its succes. After some nostalgic reminiscences, I turn to the Standard Model with a minimalistic attitude, the point of view that beyond the SM there is only the Planck scale. Known since long, the gravitational force can be obtained as the gauge theory of local Poincar\'e symmetry, called gauge gravity. This gauge theory of gravity embodies {\it per se} a Palatini formulation. This causes the potential of non-minimally coupled Higgs inflation to have an intriguing improved large field behaviour. Some of its effects are experimentally accessible or refutable. The question of quantum corrections is discussed., Comment: submitted to Acta Physica Polonica. Some cosmetic changes and typos corrected

Published
2021
Full Text
View/download PDF

23. Standard Model, and Its Standard Problems

Author

Korthals Altes, Chris P., Benedetto, John J., Series Editor, Czaja, Wojciech, Series Editor, Okoudjou, Kasso, Series Editor, Aldroubi, Akram, Editorial Board Member, Casazza, Peter, Editorial Board Member, Cochran, Douglas, Editorial Board Member, Feichtinger, Hans G., Editorial Board Member, Gilbert, Anna C., Editorial Board Member, Heil, Christopher, Editorial Board Member, Jaffard, Stéphane, Editorial Board Member, Kutyniok, Gitta, Editorial Board Member, Maggioni, Mauro, Editorial Board Member, Molter, Ursula, Editorial Board Member, Shen, Zuowei, Editorial Board Member, Strohmer, Thomas, Editorial Board Member, Unser, Michael, Editorial Board Member, Wang, Yang, Editorial Board Member, Flandrin, Patrick, editor, Paul, Thierry, editor, and Torresani, Bruno, editor

Published
2023
Full Text
View/download PDF

26. Analysis of the BraTS 2023 Intracranial Meningioma Segmentation Challenge.

Author

Dominic LaBella, Ujjwal Baid, Omaditya Khanna, Shan McBurney-Lin, Ryan McLean, Pierre Nedelec, Arif Rashid, Nourel Hoda Tahon, Talissa Altes, Radhika Bhalerao, Yaseen Dhemesh, Devon Godfrey, Fathi Hilal, Scott Floyd, Anastasia Janas, Anahita Fathi Kazerooni, John Kirkpatrick, Collin Kent, Florian Kofler, Kevin Leu, Nazanin Maleki, Bjoern H. Menze, Maxence Pajot, Zachary J. Reitman, Jeffrey D. Rudie, Rachit Saluja, Yury Velichko, Chunhao Wang, Pranav Warman, Maruf Adewole, Jake Albrecht, Udunna Anazodo, Syed Muhammad Anwar, Timothy Bergquist, Sully F. Chen, Verena Chung, Gian Marco Conte, Farouk Dako, James A. Eddy, Ivan Ezhov, Nastaran Khalili, Juan Eugenio Iglesias, Zhifan Jiang, Elaine Johanson, Koen Van Leemput, Hongwei Bran Li, Marius George Linguraru, Xinyang Liu, Aria Mahtabfar, Zeke Meier, Ahmed W. Moawad, John Mongan, Marie Piraud, Russell Takeshi Shinohara, Walter F. Wiggins, Aly H. Abayazeed, Rachel Akinola, András Jakab, Michel Bilello, Maria Correia de Verdier, Priscila Crivellaro, Christos Davatzikos, Keyvan Farahani, John B. Freymann, Christopher Hess, Raymond Y. Huang, Philipp Lohmann, Mana Moassefi, Matthew W. Pease, Philipp Vollmuth, Nico Sollmann, David Diffley, Khanak K. Nandolia, Daniel I. Warren, Ali Hussain, Pascal Fehringer, Yulia Bronstein, Lisa Deptula, Evan G. Stein, Mahsa Taherzadeh, Eduardo Portela de Oliveira, Aoife Haughey, Marinos Kontzialis, Luca Saba, Benjamin Turner, Melanie M. T. Brüßeler, Shehbaz Ansari, Athanasios Gkampenis, David Maximilian Weiss, Aya Mansour, Islam H. Shawali, Nikolay Yordanov, Joel M. Stein, Roula Hourani, Mohammed Yahya Moshebah, Ahmed Magdy Abouelatta, Tanvir Rizvi, Klara Willms, Dann C. Martin, and Abdullah Okar

Published
2024
Full Text
View/download PDF

27. The 2024 Brain Tumor Segmentation (BraTS) Challenge: Glioma Segmentation on Post-treatment MRI.

Author

Maria Correia de Verdier, Rachit Saluja, Louis Gagnon, Dominic LaBella, Ujjwal Baid, Nourel Hoda Tahon, Martha Foltyn-Dumitru, Jikai Zhang, Maram Alafif, Saif Baig, Ken Chang, Gennaro D'Anna, Lisa Deptula, Diviya Gupta, Muhammad Ammar Haider, Ali Hussain, Michael Iv, Marinos Kontzialis, Paul Manning, Farzan Moodi, Teresa Nunes, Aaron Simon, Nico Sollmann, David Vu, Maruf Adewole, Jake Albrecht, Udunna Anazodo, Rongrong Chai, Verena Chung, Shahriar Faghani, Keyvan Farahani, Anahita Fathi Kazerooni, Juan Eugenio Iglesias, Florian Kofler, Hongwei Li 0004, Marius George Linguraru, Bjoern H. Menze, Ahmed W. Moawad, Yury Velichko, Benedikt Wiestler, Talissa Altes, Patil Basavasagar, Martin Bendszus, Gianluca Brugnara, Jaeyoung Cho, Yaseen Dhemesh, Brandon K. K. Fields, Filip Garrett, Jaime Gass, Lubomir M. Hadjiiski, Jona A. Hattangadi-Gluth, Christopher Hess, Jessica L. Houk, Edvin Isufi, Lester J. Layfield, George Mastorakos, John Mongan, Pierre Nedelec, Uyen Nguyen, Sebastian Oliva, Matthew W. Pease, Aditya Rastogi, Jason Sinclair, Robert X. Smith, Leo P. Sugrue, Jonathan Thacker, Igor Vidic, Javier E. Villanueva-Meyer, Nathan S. White, Mariam Aboian, Gian Marco Conte, Anders M. Dale, Mert R. Sabuncu, Tyler M. Seibert, Brent Weinberg, Aly H. Abayazeed, Raymond Y. Huang, Sevcan Turk, Andreas M. Rauschecker, Nikdokht Farid, Philipp Vollmuth, Ayman Nada, Spyridon Bakas, Evan Calabrese, and Jeffrey D. Rudie

Published
2024
Full Text
View/download PDF

36. Free energy of a Holonomous Plasma

Author

Altes, Chris P. Korthals, Nishimura, Hiromichi, Pisarski, Robert D., and Skokov, Vladimir V.

Subjects
High Energy Physics - Phenomenology, High Energy Physics - Lattice, Nuclear Theory
Abstract

At a nonzero temperature T, a constant field $\overline{A}_0 \sim T/g$ generates nontrivial eigenvalues of the thermal Wilson line. We discuss contributions to the free energy of such a holonomous plasma when the coupling constant, $g$, is weak. We review the computation to $\sim g^2$ by several alternate methods, and show that gauge invariant sources, which are nonlinear in the gauge potential $A_0$, generate novel contributions to the gluon self energy at $\sim g^2$. These ensure the gluon self energy remains transverse to $\sim g^2$, and are essential in computing contributions to the free energy at $\sim g^3$ for small holonomy, $\overline{A}_0 \sim T$. We show that the contribution $\sim g^3$ from off-diagonal gluons is discontinuous as the holonomy vanishes. The contribution from diagonal gluons is continuous as the holonomy vanishes, but sharply constrains the possible sources which generate nonzero holonomy, and must involve an infinite number of Polyakov loops., Comment: 32 pages, 2 figures

Published
2020
Full Text
View/download PDF

38. Integrating Echocardiography Parameters With Explainable Artificial Intelligence for Data-Driven Clustering of Primary Mitral Regurgitation Phenotypes

Author

Bernard, Jérémy, Yanamala, Naveena, Shah, Rohan, Seetharam, Karthik, Altes, Alexandre, Dupuis, Marlène, Toubal, Oumhani, Mahjoub, Haïfa, Dumortier, Hélène, Tartar, Jean, Salaun, Erwan, O’Connor, Kim, Bernier, Mathieu, Beaudoin, Jonathan, Côté, Nancy, Vincentelli, André, LeVen, Florent, Maréchaux, Sylvestre, Pibarot, Philippe, and Sengupta, Partho P.

Published
2023
Full Text
View/download PDF

40. Conundrum for the free energy of a holonomous gluonic plasma at cubic order

Author

Altes, Christiaan P. Korthals, Nishimura, Hiromichi, Pisarski, Robert D., and Skokov, Vladimir V.

Subjects
High Energy Physics - Theory, High Energy Physics - Lattice, High Energy Physics - Phenomenology, Nuclear Theory
Abstract

We compute the term $\sim g^3$ in the free energy for a $SU(N)$ gauge theory with nonzero holonomy at nonzero temperature. If the holonomy is generated kinematically by the introduction of gauge invariant sources coupled to Polyakov loops, the contribution of charged (off-diagonal) gluons to the free energy at order $g^3$, ${\cal F}^{\left( 3\rm{:c.g.} \right)}$, is singular: ${\cal F}^{\left( 3\rm{:c.g.} \right)} \neq 0 $ without holonomy, but ${\cal F}^{\left( 3 \rm{:c.g.} \right)}= 0$ when the holonomy is nonzero, even infinitesimally. We show that the absence of the charged gluon contribution is required by gauge invariance alone and is therefore a universal feature., Comment: 14 pages

Published
2019
Full Text
View/download PDF

41. V13: Chronicle of a Trial by Emmanuel Carrère review -- a humane and thoughtful testimony of terror and loss; This forensic account of the 10-month-long trial of those involved in the 2015 Paris attacks, in which 130 people were killed, treads a fine line between empathy and moral judgments while shining a light on survivors' memories

Author

Henriette Korthals Altes

Subjects
Charlie Hebdo Attack, Paris, France, 2015 -- Casualties, Terrorists -- Ethical aspects, Massacres -- Casualties
Abstract

"V13" was the code name used by those who attended the monumental court proceedings that followed the 2015 Paris terror attacks in which 130 people died and 350 were injured. [...]

Published
2024

42. The Role of Chest Imaging in Patient Management During the COVID-19 Pandemic A Multinational Consensus Statement From the Fleischner Society

Author

Rubin, Geoffrey D, Ryerson, Christopher J, Haramati, Linda B, Sverzellati, Nicola, Kanne, Jeffrey P, Raoof, Suhail, Schluger, Neil W, Volpi, Annalisa, Yim, Jae-Joon, Martin, Ian BK, Anderson, Deverick J, Kong, Christina, Altes, Talissa, Bush, Andrew, Desai, Sujal R, Goldin, Jonathan, Goo, Jin Mo, Humbert, Marc, Inoue, Yoshikazu, Kauczor, Hans-Ulrich, Luo, Fengming, Mazzone, Peter J, Prokop, Mathias, Remy-Jardin, Martine, Richeldi, Luca, Schaefer-Prokop, Cornelia M, Tomiyama, Noriyuki, Wells, Athol U, and Leung, Ann N

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Patient Safety, Lung, Prevention, Infection, Good Health and Well Being, Betacoronavirus, COVID-19, Coronavirus Infections, Diagnosis, Differential, Disease Progression, Early Diagnosis, Humans, International Cooperation, Pandemics, Patient Care Management, Pneumonia, Viral, Radiography, Thoracic, Respiratory Tract Diseases, SARS-CoV-2, Tomography, X-Ray Computed, Respiratory System, Cardiovascular medicine and haematology, Clinical sciences
Abstract

With more than 900,000 confirmed cases worldwide and nearly 50,000 deaths during the first 3 months of 2020, the coronavirus disease 2019 (COVID-19) pandemic has emerged as an unprecedented health care crisis. The spread of COVID-19 has been heterogeneous, resulting in some regions having sporadic transmission and relatively few hospitalized patients with COVID-19 and others having community transmission that has led to overwhelming numbers of severe cases. For these regions, health care delivery has been disrupted and compromised by critical resource constraints in diagnostic testing, hospital beds, ventilators, and health care workers who have fallen ill to the virus exacerbated by shortages of personal protective equipment. Although mild cases mimic common upper respiratory viral infections, respiratory dysfunction becomes the principal source of morbidity and mortality as the disease advances. Thoracic imaging with chest radiography and CT are key tools for pulmonary disease diagnosis and management, but their role in the management of COVID-19 has not been considered within the multivariable context of the severity of respiratory disease, pretest probability, risk factors for disease progression, and critical resource constraints. To address this deficit, a multidisciplinary panel comprised principally of radiologists and pulmonologists from 10 countries with experience managing patients with COVID-19 across a spectrum of health care environments evaluated the utility of imaging within three scenarios representing varying risk factors, community conditions, and resource constraints. Fourteen key questions, corresponding to 11 decision points within the three scenarios and three additional clinical situations, were rated by the panel based on the anticipated value of the information that thoracic imaging would be expected to provide. The results were aggregated, resulting in five main and three additional recommendations intended to guide medical practitioners in the use of chest radiography and CT in the management of COVID-19.

Published
2020

48. Land Policy for Rural Development in the European Union and its Impact on Access to Land

Author

Korthals Altes Willem K.

Subjects
access to land, rural development, european union, land grabbing, land market, common agricultural policy, land policy, Agriculture, Social Sciences
Abstract

The concentration of farmland has potentially a negative impact on planning for local rural development as it impedes access to land for other rural initiatives. Land policies in the European Union aiming to reserve lands for local communities are constrained by principles of the EU single market, such as the free movement of capital and the freedom of establishment. Especially in several Central and Eastern European member states, the European Commission has critically reviewed policies to shield lands from the single market. This paper reviews and analysis this issue in relation to the planning for rural communities.

Published
2022
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results